The generation vs. verification delta explains why LLM's are useful
The article discusses the usefulness of large language models (LLMs) despite the need for verification. It argues that the effort required to verify LLM outputs is often less than the complexity of generating those outputs. The author believes that as long as LLMs are directionally accurate, they can significantly enhance productivity.
- ▪LLMs can be useful even if their outputs require verification.
- ▪The verification process is often simpler than the generation process.
- ▪As long as LLMs are directionally accurate, they can enhance productivity.
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The generation vs verification delta explains why LLM's are useful 05 Apr, 2026 Ever heard that you still need to verify what an LLM says so it implies that LLMs are as good as useless? I always felt that it was a lazy argument. I gave this argument some thought and I came out with an explanation that goes beyond just LLMs. I was recently looking for a word in English - I knew I had this in the tip of my tongue but was not able to find it. I asked ChatGPT to help me. This was my question: The word I was looking for was "confers". Now I don't have to explain why I don't need to verify what the LLM provided. That would be a stupid exercise. It should be clear to anyone that the LLM has genuinely helped me and there is close to zero chance of it being incorrect.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at Simian Words.
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